Simulasi Blockchain Dan Prediksi Harga Cryptocurrency Menggunakan Moving Average LSTM Serta Pengelolaan Portofolio Investasi

Tjoanda, Michael and Hendrik Fery Herdiatmoko, Fery (2025) Simulasi Blockchain Dan Prediksi Harga Cryptocurrency Menggunakan Moving Average LSTM Serta Pengelolaan Portofolio Investasi. Undergraduate thesis, Universitas Katolik Musi Charitas.

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Abstract

The growth of cryptocurrency investment in Indonesia shows rapid development; however, it still faces challenges such as low financial literacy among novice investors and high market volatility. This research aims to develop a web�based application that supports financial literacy and cryptocurrency investment portfolio management. The application integrates the Long Short-Term Memory (LSTM) algorithm Moving Average for cryptocurrency price prediction, along with video-based educational features providing learning materials and research on cryptocurrency investments. Blockchain technology is applied through the InterPlanetary File System (IPFS), specifically to store educational videos from the Academy feature and research content in a decentralized manner, ensuring data security, transparency, and accessibility. This decentralized storage approach aims to prevent data loss and enhance content availability. The application is built using Node.js, Express.js, and Python, with model training conducted on the Google Colab platform. Testing results indicate that the prediction model achieves low RMSE and MAPE values, while the integration of blockchain-based IPFS storage improves data security and content reliability.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Cryptocurrency, Long Short-Term Memory (LSTM), InterPlanetary File System (IPFS), RMSE (Root Mean Squared Error), MAPE (Mean Absolute Percentage Error
Subjects: T Technology > T Technology (General)
Divisions: Theses - S1 > Informatics Study Program
Depositing User: Michael Tjoanda
Date Deposited: 27 Feb 2025 03:40
Last Modified: 27 Feb 2025 03:40
URI: http://eprints.ukmc.ac.id/id/eprint/13566

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